2024-03-29T05:14:16Z
https://repository.dl.itc.u-tokyo.ac.jp/oai
oai:repository.dl.itc.u-tokyo.ac.jp:00000450
2022-12-19T03:41:19Z
6:32:33
9:10:14
Methods for Solving Inverse-kinematics Problems Using Nerual Networks with 0utput Error Feedback
神経回路により出力誤差のフィードバックを行う逆運動学問題の解法
大山, 英明
106561
舘, 暲
106562
548.3
Inverse-kinematics
Neural Networks
Output Feedback Inverse Model
Linear Adaptive System
application/pdf
Many studies on the learning control of the robot arm have been conducted by using neural networks, The method that uses an acquired inverse-kinematics model of the arm by learning are popular. However, acquisition of the inverse-kinematics model has a number of drawbacks. Furthermore, a limited scale neural networks system has only limited precision. Errors still remains in the output of the inverse-kinematics model using the neural networks system. In this paper, a new method for solving inverse-kinematics problem using the learned inverse model of the linearized model as output feedback system is proposed. Two possible configurations of the system are presented. The use of linear adaptive systems including Kalman filter is also proposed for higher accuracy. The performances of the proposed methods are shown by numerical simulations.
journal article
日本ロボット学会
1995-01
application/pdf
日本ロボット学会誌
1
13
89
99
AN00141189
02891824
https://repository.dl.itc.u-tokyo.ac.jp/record/450/files/1301B089.pdf
jpn